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FLANN-based adaptive threshold selection for detection of impulsive noise in images

机译:基于FLANN的自适应阈值选择,用于检测图像中的脉冲噪声

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In this paper, a novel scheme has been suggested for removing random-valued impulsive noise from images. The proposed scheme utilizes a second-order differential impulse detection followed by a recursive median filter on the corrupted pixel locations. Adaptive threshold selection from noisy image characteristics has been emphasized in this paper. A functional link artificial neural network is used for this purpose. Comparative analysis on standard images at different noise conditions shows that the proposed scheme, in general, outperforms the existing schemes. (c) 2006 Elsevier GmbH. All rights reserved.
机译:在本文中,提出了一种新颖的方案,用于从图像中去除随机值的脉冲噪声。提出的方案利用了二阶差分脉冲检测,然后在损坏的像素位置上使用了递归中值滤波器。本文强调了从噪声图像特征中自适应阈值选择。为此,使用功能链接人工神经网络。在不同噪声条件下对标准图像的比较分析表明,该方案总体上优于现有方案。 (c)2006 Elsevier GmbH。版权所有。

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